def _saving_work(self, code):
def __QA_log_info(code, end_time, start_time):
def loginfo(prefix='', astr='', listCounts=5):
if len(self._loginfolist) < listCounts:
self._loginfolist.append(astr)
else:
str = ''
for i in range(len(self._loginfolist)):
str += self._loginfolist[i] + ' '
str += astr
QA_util_log_info(prefix.format(str), self.ui_log)
self._loginfolist.clear()
prefix = '##JOB02 Saving parallelism {}_DAY ==== Trying updating\n{}'.format(
"xdxr", '{}')
loginfo(prefix, ' {} from {} to {}'.format(code, start_time,
end_time))
try:
search_cond = {'code': str(code)[0:6]}
_col = get_coll(client=None,
cacheName="stock_xdxr",
tableName="stock_xdxr")
ref_ = _col.find(search_cond)
ref_count = _col.count_documents(search_cond)
end_time = str(now_time())[0:10]
_xdxr = QA_fetch_get_stock_xdxr(str(code))
if ref_count > 0:
start_time = ref_[ref_count - 1]['date']
__QA_log_info(code, end_time, start_time)
if start_time != end_time:
# 最后一次保存的数据之后的数据
xdxrdata = _xdxr[_xdxr['date'] > start_time]
if len(xdxrdata) > 0:
_col.insert_many(QA_util_to_json_from_pandas(xdxrdata),
ordered=False)
else:
# 第一次保存数据
try:
start_time = '1990-01-01'
__QA_log_info(code, end_time, start_time)
_col.insert_many(QA_util_to_json_from_pandas(_xdxr),
ordered=False)
except Exception as e:
pass
except Exception as e:
QA_util_log_info(e.args, ui_log=self.ui_log)
self.err.append(str(code))
QA_util_log_info(self.err, ui_log=self.ui_log)
try:
# 插入前复权数据
coll_adj = get_coll(client=None,
cacheName="stock_adj",
tableName="stock_adj")
data = QA_fetch_stock_day(str(code), '1990-01-01',
str(datetime.date.today()), 'pd')
qfq = _QA_data_stock_to_fq(data, _xdxr, 'qfq')
qfq = qfq.assign(date=qfq.date.apply(lambda x: str(x)[0:10]))
adjdata = QA_util_to_json_from_pandas(
qfq.loc[:, ['date', 'code', 'adj']])
# 如果没有新增幅圈数据，插入新增数据
ref_ = coll_adj.find(search_cond)
ref_count = coll_adj.count_documents(search_cond)
if ref_count > 0:
# 历史保存过数据
lastref = ref_[ref_count - 1]
del lastref['_id']
try:
# 存在相同的数据，则保存最近数据
adjdata.index(lastref) # 找不到对应的数据，会出发异常
start_time = lastref['date']
adjdata2 = QA_util_to_json_from_pandas(qfq.loc[slice(
pd.Timestamp(start_time), pd.Timestamp(
end_time))].loc[:, ['date', 'code', 'adj']][1:])
if (ref_count + len(adjdata2)) == len(adjdata):
#
if len(adjdata2) > 0:
coll_adj.insert_many(adjdata2)
else:
raise Exception("数据总量不匹配，重新存储")
except Exception as e:
# 分红数据有变化，删除以前保存的数据，重新保存新的数据
coll_adj.delete_many({'code': code})
coll_adj.insert_many(adjdata)
else:
# 第一次保存前复权数据
# print(adjdata)
coll_adj.insert_many(adjdata)
except Exception as e:
print(e)
